Hammer and his colleagues analyzed X chromosome sequence variation and compared to autosomal sequence variation to understand the male-female asymmetrical demographic patterns observed. They believe that the large variance in male reproductive success due to wide spread practice of polygyny is the major contributing factor for sex-biased demographic pattern.

Hammer et al. used the same 90 individuals from six populations (Biaka, San, Mandenka, Han Chinese, Oceanians, and Basque) that Cox et al. analyzed, and they analyzed about 210 kb sequence from 40 independently evolving non-gene coding regions on autosomes and X chromosome.

Then, they examined the ratio of effective population size between X chromosome and autosomes (NX/NA). Note that females carry two X chromosome and males carry one X chromosome, but both sexes carry a pair of autosomal chromosome. So, the expected ratio (NX/NA) is 0.75, if male and female effective population sizes are equal. The observed ratios, on the other hand, ranges from 0.85 to 1.08 indicating that female effective population size is larger than male effective population size.

They explored the possible explanations (sequencing error, background selection, changes in population size, sex-biased migration, and high variance in male reproductive success) for the observed pattern. They believe that sequencing error is minor and background selection, changes in population size, and sex-biased migration do not alter the ratio significantly.

They hypothesize that high variance in male reproductive success is the major factor affecting the ratio, though all other factors may have contributed. They explain:

The human mating system is considered to be moderately polygynous, based on both surveys of world populations and on characteristics of human reproductive physiology. The practice of polygyny, in both the traditional sense and via ‘effective polygyny’ (whereby males tend to father children with more females than females do with males-a common practice in many contemporary western culture), would tend to increase the variance in reproductive success among males.

It is important to note that Hammer and colleagues have argued that wide spread practice of polygyny causes sex-biased demographic history, but in this article they are saying polygyny is not only cultural practice that causes some males to be reproductively more successful than the others, but they extend into other polygynous reproductive behaviors (not specific about what these cultural practices are) or physiological processes (e.g., sperm competition). In addition, age structure, lower male survival rate to the adulthood or higher mortality rate among young male, and delayed maturity of males also influence the ratio.

Another important thing to note is that Hammer and his colleagues in Cox et al. (2008) argued that female gene flow was important factor understanding human demographic history. Yet, they did not ask how female gene flow, sex-biased migration might have affected the ratio in detail, and they conducted computer simulations, but I think the two-deme island model they used is not realistic.

Cox and his colleagues analyzed X chromosome sequence variation and using isolation-with-migration (IM) model, they tried to understand how gene flow affected global genetic pattern. They found larger migration rates than they expected considering the geographic distance between each population analyzed and concluded that gene flow is an important factor for understanding human demographic history.

Cox et al. analyzed 98kb sequence from 20 independently evolving non-gene coding regions of 90 individuals from six populations (Biaka, San, Mandenka, Han Chinese, Oceanians, and Basque). They used IM, the Markov chain Mont Carlo Bayesian method to estimate effective population size of two demes and their ancestral population, asymmetrical migration rate between demes, and time of divergence since two demes sprit off. Traditional method, Fst, can be used to examine how two populations are genetically similar, but it does not differentiate effects of divergence time and gene flow. IM, on the other hand, estimates migration rates accounting for other factors, such as divergence time. Using this method, they estimated migration rates (Nm) ranging from 0.2 to 5.0 and global average of 2.4.

There are two interesting points to note. First, IM has been used for studies of human evolution, but the older version that Cox et al. used is not suitable for this. The older version of IM assumes that only two populations are exchanging genes after they were separated, but many human populations are interacting with multiple populations at the same time. The new version is released in 2010 and it allows to analyze 2-10 demes. Second, Hammer and his colleagues have argued that polygyny rather than female gene flow is the main cause for sex-biased demographic history. Since a female carries two X chromosome, X chromosome variation is largely determined by females. In this article, they have shown that female gene flow was common in our evolutionary history.

There are arguments on Afrocentrism, Eurocentrism, and criticisms against these ethnocentrisms in the online communities, such as blogs and YouTube. For example, some argue whether ancient Egyptians were black Africans or not, while others question if the first Europeans looked more like modern Africans or not. Despite anthropologists, geneticists, and educators’ efforts to eradicate racial thinking among the public, I believe that these arguments exist because of persistence of racial, or typological thinking among the human population geneticists as well as the public.

Keita and Kittles (1997) argue that racial thinking, not racist thinking, persists in the studies of human evolution through use of phylogenetic trees to show evolutionary relationship of human groups and by estimating divergence time between major racial groups(e.g. Cavalli-Sforza et al., 1994; Nei and Roychoudhury, 1993). Weiss and Long (2009) also argue that some human geneticists have replaced ‘old racial classification’ with more sophisticated scientific methods identifying human population clusters using multilocus genetic data and Structure-like population genetics methods (e.g. Rosenberg et al., 2002; Li et al., 2008).

One underlying assumption that racial thinking and clustering approach is based on is relative reproductive isolation because of lack of gene flow (e.g., Andreasen, 2004; Cavalli-Sforza et al., 1994; Risch et al., 2002). People, including human geneticists, with racial thinking believe that human populations have had very limited gene flow, where there are geographic barriers and linguistic, cultural, and political differences. They also focus on biological, genetic, linguistic, and cultural differences between different groups, while assuming that there are genetic, cultural, and linguistic similarities within a human group.

So, where did the ideas of Black Africans, Europeans, Asians…. come from? These ideas were developed based on stereotypes of people living in different parts of the world, probably very recently, after the colonial era (American Anthropological Association statement on race). Ancient Egyptians and the first Europeans probably did not have self-identities as Africans, Caucasians, or Europeans. Ancient Egypt was multi-ethnic state.

Two years after AAPA’s statement of race, American Anthropological Association (AAA) also published their statement on the race. Like AAPA statement of race, AAA statement of race follow the tradition of anthropologists and rejects the biological and genetic basis of racial classification. There are also differences between AAPA and AAA statement of race. While AAPA focuses on explaining the non-existence of biological race, AAA statement of race focuses on the historical, social, and cultural aspect of race. In this post, as I did for AAPA statement of race, I will evaluate AAA race statement with new multilocus genetic data in mind.

First, it addresses that science does not support biological and genetic basis of the race. A great amount of genetic variation exists within each racial group. There is a great deal of overlapping of phenotypic variation, because the gene flow between different groups of humans is common. Classification of humans based on physical characteristics is arbitrary and subjective.

Second, it reviews that historical context of how racial classifications are used and justified in the Western Societies. Race as a way of categorizing people is developed during the colonial era and used to rationalize social and political relationship between Europeans and conquered indigenous groups and to legitimatize the socio-political power of Europeans. Historical examples are numerous, including slavery in the U.S. and the Nazi Germany.

Finally, it stresses that today anthropologists understand that there is a great variation in human behavior, not because of genetic makeup, but because of culture, learned behavior.

The basic argument is that concept of race is socially and culturally constructed. However, they have to address why many genetic studies keep showing the genetic differences among human racial groups and why and how genetic and biological differences are maintained, if race is socially constructed.

This is the third post on the reports of Neanderthal Genome Project published on Science last week (to read previous post, click here and here). On the same edition of the science magazine that Green and colleagues published their Neanderthal genome draft sequence, Burbano and colleagues (Note that both Green et al. and Burbano et al are Paabo’s group at Max Planck Institute) address the technical issues analyzing Neanderthal genome.

Burbano et al. used different sequencing method to analyze different Neanderthal remains from Green et al. Burbano et al. used microarrays to analyze a Neanderthal remain from El Sidrón, Spain, while Green et al used shotgun sequencing technique to analyze three individuals from Vindija cave, Croatia. There are several disadvantages using the shotgun method. First, with this method, Green et al. got low coverage of Neanderthal genome sequence. Second, it is costly to have sequences of many specific loci of your interests from multiple individuals, since sequences are obtained from random fragments of DNA assembled together. Third, the shotgun sequence method does not work well, when a large amount of microbial DNA is present.

Burbano et al., on the other hand, demonstrated with microassay method that they can sequence the target locus and have more genome coverage, even with a large amount of microbial DNA. They found 88 none-synonymous substitutions in 83 genes that alter amino acid sequences, though functional consequences are not known.

Now, I understood that they could not use the shotgun sequencing method to analyze the El Sidrón individual, but I wonder why Green et al. and Burbano et al. did not combine shotgun sequencing and microassay method to analyze the three individuals from Vindija to get more genome coverage and better understanding of Neanderthal genome from these Neanderthal individuals (maybe, they are already doing it). Probably, we have to wait for a while for them to analyze more Neanderthal individuals and get more genome coverage from each. Then, we can reevaluate the genes that are unique to human and went through selective sweep. Also, we can reevaluate Neanderthal-Modern Human admixture pattern.

In addition to Neanderthal, we also have to wait to see, if they can analyze other archaic humans using either methods. Better understanding human evolution requires how other archaic humans and modern humans interacted in other parts of the world.

Green and his colleagues demonstrated what scientists can do and what kind of information you can get by applying advanced genomic technology to study of Neanderthal remains, but at the same time, we have to remind ourselves that what the Neanderthal genome tell us is still limited and hypothetical, because of small amount of DNA preserved, possible contamination from modern DNA source, chemical damage on the nucleotides, small coverage of genome, and small sample size. Another reason why it is difficult to understand Neanderthal genome is that Neanderthals are genetically very similar to modern humans. Several places in the article, the authors say that the Neanderthals are not genetically very different from modern human.

Despite the similarity, from three way comparisons of Neanderthals, modern humans, and chimpanzee, they found many genetic changes occurred only among modern human including 78 nucleotide substitutions that change amino-acid sequence (see the list on Table 2 of the article) and substitutions at regulatory area. They also found 212 regions that could have changed significantly among modern humans through strong positive selection, or selective sweep. The top 20 candidate region that selective sweep affected are listed on Table 3 of the article. These regions include genes that are responsible for metabolism, cognition, and skeletal development. However, the list will probably change, as they have more Neanderthal genome sequencing coverage and more Neanderthal individual analyzed.

Based on the closer genetic similarity between non-Africans and Neanderthal compared to between modern Africans and Neanderthals that they observed, the authors proposed that gene flow between Neanderthal and ancestors of modern non-Africans occurred. They estimated the 1 to 4 % of modern human genome is from Neanderthal and according to the authors the most likely scenario is that gene flow between Neanderthals and anatomically modern human occurred possibly in the Middle East, before ancestors of non-Africans radiated from there (Scenario 3 of Fig. 6). However, the authors also point out that actually Neanderthal genetic contribution could be smaller, if there was surfing effect, or larger, but later migration events erased evidence of ancient admixture.

Alternatively to ancient admixture, the authors also suggest that ancient population structure within Africa can also cause to have closer genetic similarity between Eurasians and Neanderthal, if the population source of the out-of-Africa had a great amount of old genetic variation that Neanderthals and modern human shared.

Now, there are several important questions that need to be addressed. If anatomically modern humans mated with Neanderthals and other archaic humans, should we considered modern humans, Neanderthals, and other archaic humans as sub-species of a single species, Homo sapience, not different species? Then, Home Sapience once had a great genetic and morphological variation, but today they are lost somehow. Should we reconsider who these archaic humans were? Once anthropologists thought intellectually superior modern humans could not be a same species as Neanderthals that had more primitive culture. However, archaeological evidence suggests that Neanderthals were capable of more complex thoughts than we originally thought. How about other archaic humans? Were they capable of having more complex culture? Are we so biased and we tend to think we are so unique and Neanderthals and other archaic humans were so different? Just like the 19th century evolutionary anthropologists who tried to theorize that Europeans were intellectually superior based on the cultural traits that they observed.

For more information, read my post on Neanderthal genome (here and here) or go to my YouTube AnthroGenetics Channel. I have a playlist on Neanderthal DNA (here). You can find videos of Green, Krause, Briggs, and Paabo talking about Neanderthal Genome project.

Last week, two articles on the Neanderthal genome were published on Science. These articles report the results of Neanderthal genome analyses that many anthropologists and human geneticists were waiting for a long time. Probably, not many anthropologists and geneticists believe the two extreme opposite view (complete replacement of archaic humans by anatomically modern humans came out of Africa within 100-200,000 years ago vs. continuous gene flow among our ancestors living in different parts of the world from the time of Homo erectus until today), but many wanted to know if archaic humans really disappeared without genetically contributing to modern human gene pool and how much gene flow, or genetic exchange, took place between anatomically modern human and archaic human, if there was. From human genetics point of view, the important question is what genetic variation is unique to modern human or what genetic variant make us human?

I am going to read through the reports and write about them this week (here for Green et al. and here for Burbano et al.), but on this post, I am going to write about the featured Science Magazine webpage, the Neandertal Genome. This webpage is recommended for non-geneticists, anthropologists, students, and general public who do not have training in genetics, because the science articles contains full of genetic terms and sophisticated analytical methods. It provides a basic background on Neanderthal and Neanderthal genome research, summary of the articles, and references. Also, it has videos of Svante Paabo, Chris Stringer, and Sarah Tishkoff talking about the methods, findings, significance,and implication of the Neanderthal genome project.

Here are some important things that these three specialists talking about the Neanderthal genome, including my comments. First, because of technical issues as well as small sample size (n=3), at this point, we do not know enough about the Neanderthal genome variation, yet, to examine, for example, if we can find evidence of our gene in the Neanderthal populations. Second, we have to understand the technical problems that they encountered, because the procedures they chose to fix the problems actually may have biased the results. Third, they estimated between 1 and 4 % of modern Eurasian genome come from Neanderthal (assuming that contamination from researchers was not problem?). This raises another question. Did ancestors of modern humans exchanged genes with other archaic humans, such as new species recently identified in Siberia? Then, how much can genetic contribution of archaic human to modern human add up? 10%?

However, this research project changed the course of how the field of anthropological genetics progress toward future. In the near future, I think the focus of the anthropological genetic research will shift from single locus non-gene coding markers, such mtDNA hypervariable region sequence and Y chromosome STR to genomics. Along with ancient genome study of extinct Eskimo individual, this project has show genomic technology can be applied to ancient DNA analysis to understand pattern of population structure as well as natural selection, hopefully at population level, not individual level.